Deutsch
English
AI support without hallucinations: grounding explained simply
A chatbot that confidently quotes the wrong shipping costs does more harm than good. The problem is called hallucination – and the solution is grounding. Here's the simple explanation, without any AI jargon.
What is a hallucination?
Language models like the one behind ChatGPT are trained to produce plausible-sounding text – not to tell the truth. If a customer asks about your return period and the model doesn't know it, it often simply invents one. That sounds convincing but is wrong. This is exactly what's called a hallucination: a fabricated answer delivered with full confidence.
In customer service that's dangerous. A false promise about shipping, warranty or price can cost you real money – and trust you'll struggle to win back.
Grounding: tying answers to sources
Grounding means: every answer must be backed by a concrete source from your knowledge base. The bot first searches your content – product descriptions, FAQ, shipping pages – and phrases its answer only from what it finds there. It's the difference between „let me guess“ and „let me check your real data“.
And when nothing is found?
That's the decisive part. A well-built bot then does not guess, but honestly admits it isn't sure and hands over to your team. Better an honest escalation than an invented answer. At Alpheris this behaviour is the default – we call the principle grounding-first.
If the AI finds no reliable answer, it says so – instead of making something up.
How to tell whether a chatbot is really grounded
- Transparency: does the system show which source was used for an answer?
- Confidence score: is there a certainty value per answer that can trigger an escalation?
- Honest gaps: does the bot say „I'm not sure about that“ instead of guessing?
These are exactly the points you test with every provider. How we handle data protection is covered in GDPR-compliant chatbots in your store.
Conclusion
Hallucinations are not a law of nature but a question of architecture. With grounding you get a bot that would rather escalate than invent – and that's precisely what makes it usable in customer service in the first place. See how it looks in practice: support automation with Alpheris.